README.md

metadata

language:
  - fr
  - en
license: mit
tags:
  - generated_from_trainer
  - summarization
datasets:
  - orange_sum
base_model: facebook/bart-large-cnn
model-index:
  - name: BART-CNN-Orangesum
    results: []

BART-CNN-Orangesum

This model is a fine-tuned version of facebook/bart-large-cnn on the orange_sum dataset. It achieves the following results on the evaluation set:

• Loss: 1.6370

It aims at improving the quality of the summary generated on French texts

Model description

this is a fine tuning of the model 'facebook/bart-large-cnn' on the 'orange_sum' dataset gives better results in French while keeping the intrinsic qualities of the BART model

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.9062	0.37	500	1.8412
1.6596	0.75	1000	1.6370

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu117
• Datasets 2.12.0
• Tokenizers 0.13.3